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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 739 records · Page 41

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NASA NTRS2019

Scheduling and Airport Taxiway Path Planning Under Uncertainty

Congestion and uncertainty on the airport surface are major constraints to the available capacity of the air transport system. This project is to study the problem of planning and scheduling airport surface movement at large airports. Specifically, we focus on the departure time scheduling and taxiway path planning of multiple aircraft under uncertainty. We also developed a simulation tool that is capable of simulating aircraft movement along the taxiway and possible uncertainty during the movement.

Li, Jiaoyang↗

NASA NTRS2019

Simulation-to-Flight 1 (STF-1): Automating the Planning, Scheduling, Assessment and Data Processing/Reduction for a Small Satellite

On December 16, 2019, a 3-U CubeSat named STF-1 launched as West Virginia's first spacecraft. This event marked the culmination of a run-up to launch involving the production of the spacecraft, creation/configuration of command and control infrastructure, and the evolution of its co-creation, the NASA Operational Simulator for Small Satellites (NOS3). This event also marked the beginning of a new phase: operations. While plans, procedures, and infrastructure were already in place or started for operations, many lessons were learned during the operations phase, especially during early operations (first month/commissioning phase). Additional plans, procedures, and infrastructure, especially related to communication planning and automated data processing, were created and developed to fill needs for the operation of the STF-1 mission.This paper and presentation will overview the STF-1 operations team's solutions to addressing the many needs of operating a low-earth orbiting CubeSat mission with a single ground antenna that is shared and scheduled with several other missions. The STF-1 operations team deployed a combination of virtualization technologies, ground station technology solutions, collaboration software, custom planning software solutions, and existing ground antenna scheduling solutions to create an effective and efficient CubeSat operations environment. The end-solution satisfied the operations stakeholders, which include NASA, its industry partner TMC Technologies, and four independent professor-student teams at West Virginia University.

CubeSat↗

NASA NTRS2019

Modeling Deicing Operations in Departure Scheduling Using Fast Time Simulation

In winter snow conditions, aircraft need inspection for deicing service before takeoff. Deicing service is a procedure to remove frost, ice, slush, or snow from aircraft for safe operation. Deicing operations vary by airport in many ways. Some airports have designated deicing zones, whereas some use a closed runway or terminal area to perform the procedure. Nonetheless, deicing operations add extra workloads to controllers, and cause increased taxi traffic on the ground. NASA and Korea Aerospace Research Institute (KARI) have been collaborating to model deicing operations at Incheon International Airport (ICN). This paper describes the deicing model and the study of deicing operations in departure scheduling using fast time simulations. The deicing model uses a heuristic algorithm for deicing zone assignment. In the fast time simulations, the model uses probability distributions derived from actual operation data to model deicing request and deicing zone time. It is envisioned that such a deicing model can be useful in airport surface scheduling to provide decision support and improve traffic management performance in winter snow operations.

modeling and simulation↗

NASA NTRS2019

Modeling Deicing Operations in Departure Scheduling using Fast Time Simulation

surface operation↗

NASA NTRS2019

STF-1 Ground Operations - Automating the Planning, Scheduling, Assessment and Data Processing/Reduction for a Small Satellite

On December 16, 2018, a 3-U CubeSat named STF-1 launched as West Virginia's first spacecraft. This event marked the culmination of a run-up to launch involving the production of the spacecraft, creation/configuration of command and control infrastructure, and the evolution of its co-creation, the NASA Operational Simulator for Small Satellites (NOS3). This event also marked the beginning of a new phase: operations. While plans, procedures, and infrastructure were already in place or started for operations, many lessons were learned during the operations phase, especially during early operations (first month/commissioning phase). Additional plans, procedures, and infrastructure, especially related to communication planning and automated data processing, were created and developed to fill needs for the operation of the STF-1 mission.This paper and presentation will overview the STF-1 operations team's solutions to addressing the many needs of operating a low-earth orbiting CubeSat mission with a single ground antenna that is shared and scheduled with several other missions. The STF-1 operations team deployed a combination of virtualization technologies, ground station technology solutions, collaboration software, custom planning software solutions, and existing ground antenna scheduling solutions to create an effective and efficient CubeSat operations environment. The end-solution satisfied the operations stakeholders, which include NASA, its industry partner TMC2 Technologies, and four independent professor-student teams at West Virginia University.

Suder, Mark↗

NASA NTRS2020

Work Scheduling and Fatigue Management

There are physiological limits to human performance, influenced by the internal programming of the sleep homeostat and circadian rhythms. There are known fatigue-related risks related to different work scheduling factors. This presentation was for presentation to supervisors and managers at Stennis Space Center to provide information about physiological risks factors associated with shiftwork scheduling practices and facilitate discussion about approaches to manage the related risks.

Gregory, Kevin↗

NASA NTRSDate not supplied

Load Schedule Design Improvements for the Calibration of NASA's Semi-span Balances

Improvements of the load schedule design for the calibration of NASA's semi-span balances are discussed. These improvements became possible after a minor hardware change was made to Calspan's Large Load Rig. This change moves normal and axial force load points 12 inches closer to the balance moment center. Resulting data quality improvements are significant because Calspan's Large Load Rig cannot currently apply forces at the balance moment center of a semi-span balance. Now, the supported set of rolling and yawing moment arms is 28 inches, 38 inches, and 48 inches. Consequently, the new load schedule design better supports expected normal and axial force locations on semi-span models that are tested in the NASA Ames 11-ft Transonic Wind Tunnel. In addition, estimates of the primary sensitivities of the normal force, axial force, rolling moment, and yawing moment have become more accurate as the applied normal and axial forces have moved closer to the balance moment center. Fundamental moment arm range requirements and Calspan's hardware updates are discussed in detail. In addition, calibration analysis results of NASA's ARC30K semi-span balance are presented to illustrate benefits of the hardware changes.

wind tunnel test↗

NASA NTRSDate not supplied

Load Schedule Design Improvements for the Calibration of NASA's Semi-span Balances

Improvements of the load schedule design for the calibration of NASA's semi-span balances are discussed. These improvements became possible after a minor hardware change was made to Calspan's Large Load Rig. This change moves normal and axial force load points 12 inches closer to the balance moment center. Resulting data quality improvements are significant because Calspan's Large Load Rig cannot currently apply forces at the balance moment center of a semi-span balance. Now, the supported set of rolling and yawing moment arms is 28, 38, and 48 inches. Consequently, the new load schedule design better supports expected normal and axial force locations on semi-span models that are tested in the NASA Ames 11-ft Transonic Wind Tunnel. In addition, estimates of the primary sensitivities of the normal force, axial force, rolling moment, and yawing moment have become more accurate as the applied normal and axial forces have moved closer to the balance moment center. Fundamental moment arm range requirements and Calspan's hardware updates are discussed. In addition, calibration and check load analysis results of NASA's ARC30K semi-span balance are presented to illustrate benefits of the hardware changes.

wind tunnel test↗

NASA NTRS2022

Fatigue, Schedules, Sleep, and Sleepiness in U.S. Commercial Pilots During COVID-19

Introduction: COVID-19 has had a significant impact on the aviation industry. While reduced flying capacity may intuitively translate to reduced fatigue risk by way of fewer flights and duty hours, the actual impact of the pandemic on pilot fatigue is unknown. Methods: We surveyed US commercial airline pilots in late 2020 (n = 669) and early 2021 (n = 156) to assess the impact of COVID-19 on schedules and fatigue during the pandemic. Results: Overall, pilots reported reduced flight and duty hours compared to pre-pandemic. Average sleep on workdays was slightly shorter in late 2020 (6.88 h) and recovered to pre-pandemic levels in early 2021 (6.95 h). Similarly, the frequency of sleepiness on days off and in-flight increased in late 2020, with 54% of pilots reporting an increase in in-flight sleepiness, then returned to pre-pandemic levels in early 2021. The use of in-flight sleepiness countermeasures remained the same across assessed time points. Pilots highlighted several factors which impacted their sleep and job performance, including limited access to nutritional food during duty days and layovers, reduced access to exercise facilities during layovers, increased stress due to job insecurity and health concerns, increased distractions and workload, and changes to scheduling. Discussion: Despite a reduction in flights and duty days, COVID-19 led to increased sleepiness on days off and in-flight, potentially due to the negative impact of lack of access to essential needs and heightened stress on sleep. Operators need to monitor the change in these COVID-19 related risks as the industry returns to full service.

sleep↗

NASA NTRS2021

Sailing Towards an Expressive Scheduling Language for Europa Clipper

The mission planners for NASA's Europa Clipper deep-space mission use automated scheduling software to generate activity plans and command sequences for multiple instruments and subsystems before sending the sequences for execution on board. Both science and engineering planners must translate their intents into expressions of mission constraints, goals, and preferences that the scheduling engine understands. This paper describes the ongoing development of a dedicated domain-specific java-embedded language that can efficiently and accurately capture such concerns for the Europa Clipper mission, along with a user-interface companion for the language.

Schaffer, Steve↗

NASA NTRS2021

An Efficient Approach for Scheduling Imaging Tasks Across a Fleet of Satellites

Dynamically retasking satellites in response to scientific alerts is challenging because the tasks and opportunities of one satellite can influence this of another. This abstract focuses on our high-level approach for scheduling imaging tasks across a constellation of satellite, which is subject to orbital and other practical constraints such as finding a feasible up-/down- link schedule. Our approach is inspired by combining insights from two existing approaches about the structure of these problems to create an efficient, new approach. We show that our approach stacks up favorably against two baselines–an optimal solver as well as a naive, greedy approach.

Maillard, Adrien↗

NASA NTRSDate not supplied

The Human Research Program Grant Lifecycle & Data Integration Schedule: Infographic

The Human Research Program (HRP) Grant Lifecycle process can be described using information from several government authoritative sources with overlapping generalizations. It is the responsibility of the HRP Program Planning & Control (PP&C) Office and the Data Management Integration Office (DMIO)to interpret this information into a cohesive process that can be communicated to the human research organization. PP&C and DMIO have been exploring training opportunities to facilitate understanding through the form of infographics. This communication tool combines eye-catching visuals and text making complex information and data more digestible and shareable. The infographic poster tells a short story about a federally awarded grant and is intended to help both the new and experienced HRP workforce understand the timeline for a research procurement and where their specific tasks fall within the 4 phases of the grant lifecycle. The Pre-Award, Award, Post-Award, and Closeout phases are overlayed with business swimlanes so HRP stakeholders can see where they fit into the timeline rather than working in an isolated part. This includes the Chief Scientist Office (CSO), PP&C, the Data Management Integration Office (DMIO), the Principal Investigator (PI), the Element stakeholders, the LSDA Archivists, and the Research & Operations Integration (ROI) team along with the stakeholders in the Human Health and Performance Directorate. Additionally, the poster introduces (1) the HRP Data Integration Schedule identified in the HRP Data Management Plan HRP-48047, Table 8-2 and (2) a Smartsheet Solution to automate the grants tracking business process. Emphasis is given to the Data Integration Schedule which is the basis for the milestone tasks that are to be completed during the Post-Award phase in the grant lifecycle. The poster is also an opportunity to present the Smartsheet Solution, a software collaboration and work management tool used to assign tasks and track project progress. This PP&C FY24 effort will facilitate an end-to-end solution to track grants and provide insight to the health of HRP grant research procurements using metrics, reports, and dashboards.

J Peace↗

DOE OSTI2020

Cooperative Load Scheduling for Multiple Aggregators Using Hierarchical ADMM

Demand response (DR) serves an important role in improving the efficiency and stability of power systems. In recent years, with advances in communication and smart device technologies, many aggregators have emerged to facilitate end customer participation in DR programs. These aggregators, equipped with customized optimal control algorithms, are capable of providing various grid services. Among them is load scheduling during DR events, namely following a load signal provided by the utility company while minimizing overall customer discomfort. However, as the number of aggregators keeps increasing, it becomes challenging for utility companies to conduct load scheduling for multiple aggregators and generate reference signals for each of them. This paper proposes an optimization framework using hierarchical alternating direction method of multipliers (H-ADMM) to optimally generate load following signals for multiple aggregators. Under this framework, utility and multiple aggregators work in a cooperative manner, aiming at minimizing an overall system cost from different levels of the power system hierarchy, while protecting user privacy. A case study has been conducted in a system with multiple aggregators, based on control of HVAC loads. Experimental results validate the effectiveness of the proposed algorithm.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

System and method for optimal load and source scheduling in context aware homes

A controller for controlling energy consumption in a home includes a constraints engine to define variables for multiple appliances in the home corresponding to various home modes and persona of an occupant of the home. A modeling engine models multiple paths of energy utilization of the multiple appliances to place the home into a desired state from a current context. An optimal scheduler receives the multiple paths of energy utilization and generates a schedule as a function of the multiple paths and a selected persona to place the home in a desired state.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2020

On-the fly scheduling of execution of dynamic hardware behaviors

Methods for dynamically executing computer code across multiple disparate processing unit architectures are disclosed. During execution of a first portion of computer code on a first processing unit, it is determined that a first dynamic hardware behavior of a plurality of dynamic hardware behaviors will occur at a subsequent point in time, based on a second dynamic hardware behavior that is occurring. The methods include determining to execute code corresponding to the first dynamic hardware behavior on a second processing unit, rather than the first processing unit, and scheduling computer program code corresponding to the first dynamic hardware behavior to execute on the second processing unit rather than the first processing unit. Upon completion of execution of the computer code corresponding to the first dynamic hardware behavior, a remaining portion of the computer code is scheduled to execute on the first processing unit.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Fuzzified PaCcET for Economic-Emission Scheduling of Microgrids

In this paper, a new approach is proposed to solve a multi-objective economic-emission scheduling problem in microgrids (MGs) by simultaneously minimizing the energy and emission costs of the MG with various distributed energy resources (DERs). The proposed approach is an extension of a computationally effective multiobjective optimization technique, Pareto concavity elimination transformation (PaCcET). The proposed approach, referred to as Fuzzified-PaCcET, employs a fuzzy logic controller to dynamically revise crossover and mutation rates in the original PaCcET leading to the faster convergence of the solution. The proposed approach finds the best Pareto front, also referred to as a Non-dominated set (NDS) of solutions, instead of finding a single optimal solution. In order to find the solutions on concave areas of the Pareto front, an iterative objective space transformation is performed in the PaCcET algorithm to allow a linear combination of objective functions (in the transformed objective space). The proposed Fuzzified-PaCcET-based scheduling is implemented on a MG with various dispatchable and non-dispatchable DERs to find the set of optimal solutions according to the total fuel cost of DERs, as well as the most optimum environmental cost. In order to extract the best compromise solution (BCS) among NDS of solutions, a fuzzy-based method is implemented. The comparison of the simulation results of the Fuzzified-PaCcET with that of PaCcET shows that Fuzzified-PaCcET can generate better solution with less computational burden.

42 ENGINEERING↗

DOE OSTI2020

Scheduling and Control of Flexible Building Loads for Grid Services Based on a Virtual Battery Model

This paper presents a framework for modeling, scheduling, and controlling residential thermostatically controlled loads (TCLs) to provide multiple grid services, such as energy shifting, peak load reduction, and ancillary services. A modeling method is proposed to characterize the aggregate flexibility from heterogeneous TCLs using a battery-equivalent model. Based on the flexibility model, a multi-period optimal scheduling formulation is developed to best utilize the flexibility from building loads and maximize total benefits from stacked value streams. An algorithm is proposed to control individual TCLs to follow the desired power consumption in real-time. The proposed methods are illustrated and validated through simulations.

Wu, Di↗

DOE OSTI2022

Systems and methods for tensor scheduling

A technique for efficient scheduling of operations in a program for parallelized execution thereof using a multi-processor runtime environment having two or more processors includes constraining the type or number of loop optimization transforms that may be explored such that memory and processing capacity available for the scheduling task are not exceeded, while facilitating a tradeoff between memory locality, parallelization, and/or data communication between memory modules of the multi-processor runtime environment.

Meister, Benoit J.↗